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A Survey on the Security Issues of QUIC

2022· article· en· W4310172306 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInternet Traffic Analysis and Secure E-voting
Canadian institutionsConcordia University
Fundersnot available
KeywordsComputer scienceUser Datagram ProtocolHypertext Transfer ProtocolComputer networkProtocol (science)Transport Layer SecurityComputer securityThe InternetInternet ProtocolWorld Wide Web

Abstract

fetched live from OpenAlex

A newly established multiplexed network protocol - QUIC, which is based on User Datagram Protocol (UDP), has emerged in recent years and gained a large share of Internet traffic quickly. Initially proposed by Google, the goal of QUIC is to achieve a higher Internet communication performance and eventually replace the Transmission Control Protocol (TCP) + Transport Layer Security (TLS) + HTTP/2 architecture. In particular, the 3 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rd</sup> version of the Hypertext Transfer Protocol - HTTP/3.0 is built on top of QUIC. A good number of research papers have been published recently to evaluate the performance and security of the QUIC protocol. In this paper, we conduct a comprehensive survey on the QUIC security issues and analyze its future research directions regarding security prospective. We investigate several topics including the QUIC protocol structure, QUIC security model, security issues related to QUIC protocol, and future research directions on QUIC Security. To the best of our knowledge, it is the one of first surveys that focus on the security of the QUIC protocol.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.990
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.261
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it